In wireless communication systems, transmission techniques involving multiple antennas are often categorized as open-loop or closed-loop, depending on the level or degree of channel response information used by the transmission algorithm. Open-loop techniques do not rely on the information of the spatial channel response between the transmitting device and the receiving device. They typically involve either no feedback or the feedback of the long term statistical information that a base unit may use to choose between different open loop techniques. Open-loop techniques include transmit diversity, delay diversity, and space-time coding techniques such as the Alamouti space-time block code.
Closed-loop transmission techniques utilize knowledge of the channel response to weight the information transmitted from multiple antennas. To enable a closed-loop transmit array to operate adaptively, the array must apply the transmit weights derived from the channel response, its statistics or characteristics, or a combination thereof. There are several methodologies for enabling closed-loop transmission. These are discussed in the context of the downlink of a cellular communication system in which a base station (BS) (sometimes referred to as a base unit or access point or node-B or eNode-B) with multiple antennas transmits to a mobile station (MS) (sometimes referred to as a mobile or remote unit or user equipment or UE) having one or more receive antennas and one or more transmit antennas. The MS may not necessarily have the same number of transmit antennas as receive antennas. Exemplary closed-loop methodologies include adaptive transmit beam-forming, closed-loop single-user MIMO, closed-loop multi-user MIMO, and coordinated multi-point transmission (or CoMP). In these examples, the transmitter applies weighting coefficients that are derived according to an optimization algorithm to control characteristics of the transmitted signal energy.
One methodology for enabling closed-loop transmission is codebook index feedback in which both the BS and MS maintain one or more finite codebooks of possible transmit weight vectors or matrices, depending on the number of simultaneous transmit beams being formed. The MS measures the downlink multi-antenna channel response and computes the transmit weight vector or matrix that is best suited to transmit information to itself. Specifically a MS chooses the best transmit weight vector or matrix to optimize the data reception performance when the same transmit weight vector or matrix is used by the BS to transmit data to the MS. An MS may also choose multiple elements (vectors or matrices) from one or more codebooks and combine them to construct a single transmit weight vector or matrix. While choosing multiple elements the goal is to optimize the data reception performance when the transmit weight vector or matrix as constructed from the combination is used by the BS to transmit data to the MS. The MS then transmits the index into the codebook back to the BS, where the index into the codebook is often called a Precoding Matrix Index (PMI). The BS uses the transmit weight vector or matrix corresponding to the index fed back by the MS. The particular codebook that a MS and a BS uses may change from time to time. The BS has the flexibility to change the transmit weight vector or matrix recommended by the MS for transmission. Codebook index feedback can be applied to both frequency division duplex (FDD) and time division duplex (TDD) systems. The PMI based codebook feedback methods are used with a CQI and a rank indication (RI) feedback. The CQI represents the modulation and coding scheme (MCS) of the transport blocks and includes the effect of precoding as will as receiver processing. The rank indication (RI) represents the rank of the precoding matrix that maximizes the data-rate.
Another methodology for enabling closed-loop transmission is direct channel feedback (DCFB), wherein the MS measures the downlink channel response and encodes that channel response as an analog signal to be conveyed on the uplink. The downlink channel response estimates are encoded along with known pilot signals that enable the BS to estimate the analog values of the downlink channel estimates. DCFB can be applied to both FDD and TDD systems.
Another methodology for enabling closed-loop transmission is analog covariance matrix or analog eigenvector feedback. In covariance feedback the MS measures the downlink channel response, computes a covariance matrix for the band of interest, and then feeds back the values of the covariance matrix in an analog fashion to the BS. For eigenvector feedback, the MS obtains a covariance matrix similar to that of covariance feedback but then computes the dominant eigenvector or eigenvectors of the covariance matrix and feeds back the eigenvector or eigenvectors in an analog fashion to the BS.
Another methodology for enabling closed-loop transmission is quantized eigenvector feedback. In this method the eigenvectors of the channel covariance matrix is quantized (using vector quantization) to one or more vectors or matrices and sent back to the BS. The objective for the quantization method is to accurately represent the dominant eigenvectors of the covariance matrix.
Yet another methodology for enabling closed-loop transmission is to quantize the elements of the covariance matrix by a fixed number of bits with fixed and predefined amplitude and phase range. Specifically the quantization function that maps an unquantized value or a set of values to a quantized value or a set of values is predefined and fixed for a given size of the covariance matrix. In addition the quantization of one element of the covariance matrix or a set of elements of the covariance matrix does not depend on the quantization of the elements outside the set. Then the MS feeds back the fixed number of bits and the BS is able to get a one-time estimate of the covariance matrix which tends to have fairly high quantization error.
Another methodology for enabling closed-loop transmission is to use codebook based feedback for quantization of a covariance matrix. The codebooks contain vectors or matrices that are predetermined and known to the BS and the MS. A covariance matrix is estimated at the MS and is quantized using a combination (or function) of vectors or matrices with the same rank weighted by scalars. Specifically a weighted sum of the outer products of vectors or matrices with the same rank is used to represent a covariance matrix. In this case the spatial channel information is conveyed by multiple codebook indices and one or more scalars. Along with the spatial information, a CQI representing the quality of the channel without precoding may be fed back to help determine MCS at the BS. A rank indication (RI) representing the rank of precoding may or may not be fed back.
The codebook-based techniques described above can be classified into two groups—(i) PMI based methods that do not provide the rich channel information provided by covariance feedback but these methods are compatible with CQI feedback representing MCS of the transport blocks including the effect of precoding and receiver processing and (ii) the covariance quantization based methods that are not compatible with CQI and rank indication feedback representing the MCS of the transport blocks including the effect of precoding. Hence a method is needed to obtain the channel quality of covariance-based feedback with the simple and elegant feedback of the codebook-based methods and which is compatible with CQI feedback representing MCS of the transport blocks including the effect of precoding and receiver processing and RI feedback representing the rank of precoding.
Skilled artisans will appreciate that elements in the figures are illustrated for simplicity and clarity and have not necessarily been drawn to scale. For example, the dimensions and/or relative positioning of some of the elements in the figures may be exaggerated relative to other elements to help to improve understanding of various embodiments of the present invention. Also, common but well-understood elements that are useful or necessary in a commercially feasible embodiment are often not depicted in order to facilitate a less obstructed view of these various embodiments of the present invention. It will further be appreciated that certain actions and/or steps may be described or depicted in a particular order of occurrence while those skilled in the art will understand that such specificity with respect to sequence is not actually required. Those skilled in the art will further recognize that references to specific implementation embodiments such as “circuitry” may equally be accomplished via replacement with software instruction executions either on general purpose computing apparatus (e.g., CPU) or specialized processing apparatus (e.g., DSP). It will also be understood that the terms and expressions used herein have the ordinary technical meaning as is accorded to such terms and expressions by persons skilled in the technical field as set forth above except where different specific meanings have otherwise been set forth herein.